Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
Photography
Realism
Style
wavymulder
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yntec/AnalogDiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/AnalogDiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Yntec/AnalogDiffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Update vae/config.json
Browse files- vae/config.json +1 -3
vae/config.json
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@@ -1,6 +1,6 @@
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{
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"_class_name": "AutoencoderKL",
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"_diffusers_version": "0.
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"act_fn": "silu",
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"block_out_channels": [
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128,
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"force_upcast": true,
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"in_channels": 3,
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"latent_channels": 4,
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"latents_mean": null,
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"latents_std": null,
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"layers_per_block": 2,
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"norm_num_groups": 32,
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"out_channels": 3,
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{
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"_class_name": "AutoencoderKL",
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"_diffusers_version": "0.25.0.dev0",
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"act_fn": "silu",
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"block_out_channels": [
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128,
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"force_upcast": true,
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"in_channels": 3,
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"latent_channels": 4,
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"layers_per_block": 2,
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"norm_num_groups": 32,
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"out_channels": 3,
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